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At least 55 records · Page 3

A New Organization Metric for Synoptic Scale Tropical Convective Aggregation

Organization metrics were originally developed to measure how densely convective clouds are arranged at mesoscales. In this work, we apply organization metrics to describe tropical synoptic scale convective activity. Such activity is identified by cloud-precipitation (hybrid) regimes defined at 1-degree and 1-hourly resolution. Existing metrics were found to perform inadequately for such convective regime aggregates because the large domain size and co-existence of sparse aggregate occurrences with noisy isolated convection often violate assumptions inherent in these metrics. In order to capture these characteristics, in this study the existing “convective organization potential” (COP) metric was modified so as to focus on local organization and provide increased weight to aggregate size. The resulting “area-based COP” (ABCOP) follows the principle that the more numerous the objects, the higher the chance of organization. It is thus optimized to capture large-scale convective events occurring during phenomena such as ENSO and MJO, while also performs as well as existing metrics for small domain sizes.

Synoptic scales↗

Handbook of aircraft noise metrics

Information is presented on 22 noise metrics that are associated with the measurement and prediction of the effects of aircraft noise. Some of the instantaneous frequency weighted sound level measures, such as A-weighted sound level, are used to provide multiple assessment of the aircraft noise level. Other multiple event metrics, such as day-night average sound level, were designed to relate sound levels measured over a period of time to subjective responses in an effort to determine compatible land uses and aid in community planning. The various measures are divided into: (1) instantaneous sound level metrics; (2) duration corrected single event metrics; (3) multiple event metrics; and (4) speech communication metrics. The scope of each measure is examined in terms of its: definition, purpose, background, relationship to other measures, calculation method, example, equipment, references, and standards.

Bennett, R. L.↗

The independence of software metrics taken at different life-cycle stages

Over the past few years a large number of software metrics have been proposed and, in varying degrees, a number of these metrics have been subjected to empirical validation which demonstrated the utility of the metrics in the software development process. Attempts to classify these metrics and to determine if the metrics in these different classes appear to be measuring distinct attributes of the software product are studied. Statistical analysis is used to determine the degree of relationship among the metrics.

Kafura, D.↗

Metric analysis and data validation across FORTRAN projects

The desire to predict the effort in developing or explaining the quality of software has led to the proposal of several metrics. As a step toward validating these metrics, the Software Engineering Laboratory (SEL) has analyzed the software science metrics, cyclomatic complexity, and various standard program measures for their relation to effort (including design through acceptance testing), development errors (both discrete and weighted according to the amount of time to locate and fix), and one another. The data investigated are collected from a project FORTRAN environment and examined across several projects at once, within individual projects and by reporting accuracy checks demonstrating the need to validate a database. When the data comes from individual programmers or certain validated projects, the metrics' correlations with actual effort seem to be strongest. For modules developed entirely by individual programmers, the validity ratios induce a statistically significant ordering of several of the metrics' correlations. When comparing the strongest correlations, neither software science's E metric cyclomatic complexity not source lines of code appears to relate convincingly better with effort than the others.

Basili, Victor R.↗

Fighter agility metrics, research, and test

Proposed new metrics to assess fighter aircraft agility are collected and analyzed. A framework for classification of these new agility metrics is developed and applied. A completed set of transient agility metrics is evaluated with a high fidelity, nonlinear F-18 simulation provided by the NASA Dryden Flight Research Center. Test techniques and data reduction methods are proposed. A method of providing cuing information to the pilot during flight test is discussed. The sensitivity of longitudinal and lateral agility metrics to deviations from the pilot cues is studied in detail. The metrics are shown to be largely insensitive to reasonable deviations from the nominal test pilot commands. Instrumentation required to quantify agility via flight test is also considered. With one exception, each of the proposed new metrics may be measured with instrumentation currently available. Simulation documentation and user instructions are provided in an appendix.

Liefer, Randall K.↗

A Validation of Object-Oriented Design Metrics

This paper presents the results of a study conducted at the University of Maryland in which we experimentally investigated the suite of Object-Oriented (00) design metrics introduced by [Chidamber and Kemerer, 1994]. In order to do this, we assessed these metrics as predictors of fault-prone classes. This study is complementary to [Lieand Henry, 1993] where the same suite of metrics had been used to assess frequencies of maintenance changes to classes. To perform our validation accurately, we collected data on the development of eight medium-sized information management systems based on identical requirements. All eight projects were developed using a sequential life cycle model, a well-known 00 analysis/design method and the C++ programming language. Based on experimental results, the advantages and drawbacks of these 00 metrics are discussed and suggestions for improvement are provided. Several of Chidamber and Kemerer's 00 metrics appear to be adequate to predict class fault-proneness during the early phases of the life-cycle. We also showed that they are, on our data set, better predictors than "traditional" code metrics, which can only be collected at a later phase of the software development processes.

Basili, Victor R.↗

A Validation of Object-Oriented Design Metrics as Quality Indicators

This paper presents the results of a study in which we empirically investigated the suits of object-oriented (00) design metrics introduced in another work. More specifically, our goal is to assess these metrics as predictors of fault-prone classes and, therefore, determine whether they can be used as early quality indicators. This study is complementary to the work described where the same suite of metrics had been used to assess frequencies of maintenance changes to classes. To perform our validation accurately, we collected data on the development of eight medium-sized information management systems based on identical requirements. All eight projects were developed using a sequential life cycle model, a well-known 00 analysis/design method and the C++ programming language. Based on empirical and quantitative analysis, the advantages and drawbacks of these 00 metrics are discussed. Several of Chidamber and Kamerer's 00 metrics appear to be useful to predict class fault-proneness during the early phases of the life-cycle. Also, on our data set, they are better predictors than 'traditional' code metrics, which can only be collected at a later phase of the software development processes.

Basili, Victor R.↗

Testing, Requirements, and Metrics

The criticality of correct, complete, testable requirements is a fundamental tenet of software engineering. Also critical is complete requirements based testing of the final product. Modern tools for managing requirements allow new metrics to be used in support of both of these critical processes. Using these tools, potential problems with the quality of the requirements and the test plan can be identified early in the life cycle. Some of these quality factors include: ambiguous or incomplete requirements, poorly designed requirements databases, excessive or insufficient test cases, and incomplete linkage of tests to requirements. This paper discusses how metrics can be used to evaluate the quality of the requirements and test to avoid problems later. Requirements management and requirements based testing have always been critical in the implementation of high quality software systems. Recently, automated tools have become available to support requirements management. At NASA's Goddard Space Flight Center (GSFC), automated requirements management tools are being used on several large projects. The use of these tools opens the door to innovative uses of metrics in characterizing test plan quality and assessing overall testing risks. In support of these projects, the Software Assurance Technology Center (SATC) is working to develop and apply a metrics program that utilizes the information now available through the application of requirements management tools. Metrics based on this information provides real-time insight into the testing of requirements and these metrics assist the Project Quality Office in its testing oversight role. This paper discusses three facets of the SATC's efforts to evaluate the quality of the requirements and test plan early in the life cycle, thus preventing costly errors and time delays later.

Rosenberg, Linda↗

A Sensor-Independent Gust Hazard Metric

A procedure for calculating an intuitive hazard metric for gust effects on airplanes is described. The hazard metric is for use by pilots and is intended to replace subjective pilot reports (PIREPs) of the turbulence level. The hazard metric is composed of three numbers: the first describes the average airplane response to the turbulence, the second describes the positive peak airplane response to the gusts, and the third describes the negative peak airplane response to the gusts. The hazard metric is derived from any time history of vertical gust measurements and is thus independent of the sensor making the gust measurements. The metric is demonstrated for one simulated airplane encountering different types of gusts including those derived from flight data recorder measurements of actual accidents. The simulated airplane responses to the gusts compare favorably with the hazard metric.

Stewart, Eric C.↗

Evaluation of Standard Gear Metrics in Helicopter Flight Operation

Each false alarm made by a machine monitoring system carries a high price tag. The machine must be taken out of service, thoroughly inspected with possible disassembly, and then made ready for service. Loss of use of the machine and the efforts to inspect it are costly. In addition, if a monitoring system is prone to false alarms, the system will soon be turned off or ignored. For aircraft applications, one growing concern is that the dynamic flight environment differs from the laboratory environment where fault detection methods are developed and tested. Vibration measurements made in flight are less stationary than those made in a laboratory, or test facility, and thus a given fault detection method may produce more false alarms in flight than might be anticipated. In 1977. Stewart introduced several metrics, including FM0 and FM4, for evaluating the health of a gear. These metrics are single valued functions of the vibration signal that indicate if the signal deviates from an ideal model of the signal. FM0 is a measure of the ratio of the peak-to-peak level to the harmonic energy in the signal. FM4 is the kurtosis of the signal with the gear mesh harmonics and first order side bands removed. The underlying theory is that a vibration signal from a gear in good condition is expected to be dominated by a periodic signal at the gear mesh frequency. If one or a small number of gear teeth contain damage or faults, the signal will change, possibly showing increased amplitude, local phase changes or both near the damaged region of the gear. FM0 increases if a signal contains a local increase in amplitude. FM4 increases if a signal contains a local increase in amplitude or local phase change in a periodic signal. Over the years, other single value metrics were also introduced to detect the onset and growth of damage in gears. These various metrics have detected faults in several gear tests in experimental test rigs. Conditions in these tests have been steady state in the sense that the rpm, torque and forces on the gear have been held steady. For gears used in a dynamic environment such as that occurring in aircraft, the rpm, torque and forces on the gear are constantly changing. The authors have measured significant variation in rpm and torque in the transmissions of helicopters in controlled steady flight conditions flown by highly proficient test pilots. Statistical analyses of the data taken in flight show significant nonstationarity in the vibration measurements. These deviations from stationarity may increase false alarms in gear monitoring during aircraft flight. In the proposed paper, the authors will study vibration measurements made in flight on an AH- 1 Cobra and an OH-58C Kiowa helicopters. The primary focus will be the development of a methodology to assess the impact of nonstationarity on false alarms. Issues to be addressed include how time synchronous averages are constructed from raw data as well as how lack of stationarity effects the behavior of single value metrics. Emphasis will be placed on the occurrence of false alarms with the use of standard metrics. In order to maintain an acceptable level of false alarms in the flight environment, this study will also address the determination of appropriate threshold levels, which may need to be higher than for test rigs.

Mosher, M.↗

NASA Aviation Safety Program Systems Analysis/Program Assessment Metrics Review

The goal of this project is to evaluate the metrics and processes used by NASA's Aviation Safety Program in assessing technologies that contribute to NASA's aviation safety goals. There were three objectives for reaching this goal. First, NASA's main objectives for aviation safety were documented and their consistency was checked against the main objectives of the Aviation Safety Program. Next, the metrics used for technology investment by the Program Assessment function of AvSP were evaluated. Finally, other metrics that could be used by the Program Assessment Team (PAT) were identified and evaluated. This investigation revealed that the objectives are in fact consistent across organizational levels at NASA and with the FAA. Some of the major issues discussed in this study which should be further investigated, are the removal of the Cost and Return-on-Investment metrics, the lack of the metrics to measure the balance of investment and technology, the interdependencies between some of the metric risk driver categories, and the conflict between 'fatal accident rate' and 'accident rate' in the language of the Aviation Safety goal as stated in different sources.

Louis, Garrick E.↗

Towards a Visual Quality Metric for Digital Video

The advent of widespread distribution of digital video creates a need for automated methods for evaluating visual quality of digital video. This is particularly so since most digital video is compressed using lossy methods, which involve the controlled introduction of potentially visible artifacts. Compounding the problem is the bursty nature of digital video, which requires adaptive bit allocation based on visual quality metrics. In previous work, we have developed visual quality metrics for evaluating, controlling, and optimizing the quality of compressed still images. These metrics incorporate simplified models of human visual sensitivity to spatial and chromatic visual signals. The challenge of video quality metrics is to extend these simplified models to temporal signals as well. In this presentation I will discuss a number of the issues that must be resolved in the design of effective video quality metrics. Among these are spatial, temporal, and chromatic sensitivity and their interactions, visual masking, and implementation complexity. I will also touch on the question of how to evaluate the performance of these metrics.

Watson, Andrew B.↗

Metrics for Linear Kinematic Features in Sea Ice

The treatment of leads as cracks or discontinuities (see Coon et al. presentation) requires some shift in the procedure of evaluation and comparison of lead-resolving models and their validation against observations. Common metrics used to evaluate ice model skills are by and large an adaptation of a least square "metric" adopted from operational numerical weather prediction data assimilation systems and are most appropriate for continuous fields and Eilerian systems where the observations and predictions are commensurate. However, this class of metrics suffers from some flaws in areas of sharp gradients and discontinuities (e.g., leads) and when Lagrangian treatments are more natural. After a brief review of these metrics and their performance in areas of sharp gradients, we present two new metrics specifically designed to measure model accuracy in representing linear features (e.g., leads). The indices developed circumvent the requirement that both the observations and model variables be commensurate (i.e., measured with the same units) by considering the frequencies of the features of interest/importance. We illustrate the metrics by scoring several hypothetical "simulated" discontinuity fields against the lead interpreted from RGPS observations.

Levy, G.↗

Evaluating Algorithm Performance Metrics Tailored for Prognostics

Prognostics has taken a center stage in Condition Based Maintenance (CBM) where it is desired to estimate Remaining Useful Life (RUL) of the system so that remedial measures may be taken in advance to avoid catastrophic events or unwanted downtimes. Validation of such predictions is an important but difficult proposition and a lack of appropriate evaluation methods renders prognostics meaningless. Evaluation methods currently used in the research community are not standardized and in many cases do not sufficiently assess key performance aspects expected out of a prognostics algorithm. In this paper we introduce several new evaluation metrics tailored for prognostics and show that they can effectively evaluate various algorithms as compared to other conventional metrics. Specifically four algorithms namely; Relevance Vector Machine (RVM), Gaussian Process Regression (GPR), Artificial Neural Network (ANN), and Polynomial Regression (PR) are compared. These algorithms vary in complexity and their ability to manage uncertainty around predicted estimates. Results show that the new metrics rank these algorithms in different manner and depending on the requirements and constraints suitable metrics may be chosen. Beyond these results, these metrics offer ideas about how metrics suitable to prognostics may be designed so that the evaluation procedure can be standardized. 1

Saxena, Abhinav↗

On Applying the Prognostic Performance Metrics

Prognostics performance evaluation has gained significant attention in the past few years. As prognostics technology matures and more sophisticated methods for prognostic uncertainty management are developed, a standardized methodology for performance evaluation becomes extremely important to guide improvement efforts in a constructive manner. This paper is in continuation of previous efforts where several new evaluation metrics tailored for prognostics were introduced and were shown to effectively evaluate various algorithms as compared to other conventional metrics. Specifically, this paper presents a detailed discussion on how these metrics should be interpreted and used. Several shortcomings identified, while applying these metrics to a variety of real applications, are also summarized along with discussions that attempt to alleviate these problems. Further, these metrics have been enhanced to include the capability of incorporating probability distribution information from prognostic algorithms as opposed to evaluation based on point estimates only. Several methods have been suggested and guidelines have been provided to help choose one method over another based on probability distribution characteristics. These approaches also offer a convenient and intuitive visualization of algorithm performance with respect to some of these new metrics like prognostic horizon and alpha-lambda performance, and also quantify the corresponding performance while incorporating the uncertainty information.

Saxena, Abhinav↗

Metrics for Offline Evaluation of Prognostic Performance

Prognostic performance evaluation has gained significant attention in the past few years. Currently, prognostics concepts lack standard definitions and suffer from ambiguous and inconsistent interpretations. This lack of standards is in part due to the varied end-user requirements for different applications, time scales, available information, domain dynamics, etc. to name a few. The research community has used a variety of metrics largely based on convenience and their respective requirements. Very little attention has been focused on establishing a standardized approach to compare different efforts. This paper presents several new evaluation metrics tailored for prognostics that were recently introduced and were shown to effectively evaluate various algorithms as compared to other conventional metrics. Specifically, this paper presents a detailed discussion on how these metrics should be interpreted and used. These metrics have the capability of incorporating probabilistic uncertainty estimates from prognostic algorithms. In addition to quantitative assessment they also offer a comprehensive visual perspective that can be used in designing the prognostic system. Several methods are suggested to customize these metrics for different applications. Guidelines are provided to help choose one method over another based on distribution characteristics. Various issues faced by prognostics and its performance evaluation are discussed followed by a formal notational framework to help standardize subsequent developments.

Saxena, Abhinav↗

Semantic Metrics for Analysis of Software

A recently conceived suite of object-oriented software metrics focus is on semantic aspects of software, in contradistinction to traditional software metrics, which focus on syntactic aspects of software. Semantic metrics represent a more human-oriented view of software than do syntactic metrics. The semantic metrics of a given computer program are calculated by use of the output of a knowledge-based analysis of the program, and are substantially more representative of software quality and more readily comprehensible from a human perspective than are the syntactic metrics.

Etzkorn, Letha H.↗

Up Periscope! Designing a New Perceptual Metric for Imaging System Performance

Modern electronic imaging systems include optics, sensors, sampling, noise, processing, compression, transmission and display elements, and are viewed by the human eye. Many of these elements cannot be assessed by traditional imaging system metrics such as the MTF. More complex metrics such as NVTherm do address these elements, but do so largely through parametric adjustment of an MTF-like metric. The parameters are adjusted through subjective testing of human observers identifying specific targets in a set of standard images. We have designed a new metric that is based on a model of human visual pattern classification. In contrast to previous metrics, ours simulates the human observer identifying the standard targets. One application of this metric is to quantify performance of modern electronic periscope systems on submarines.

imaging↗